Machine-Learning with python (jupyter)

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Machine-Learning with python (jupyter)

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HyeonWoo Jeong
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HyeonWoo Jeong
Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

MLJAR 2.4k Jan 02, 2023
Fast Fourier Transform-accelerated Interpolation-based t-SNE (FIt-SNE)

FFT-accelerated Interpolation-based t-SNE (FIt-SNE) Introduction t-Stochastic Neighborhood Embedding (t-SNE) is a highly successful method for dimensi

Kluger Lab 547 Dec 21, 2022
An implementation of Relaxed Linear Adversarial Concept Erasure (RLACE)

Background This repository contains an implementation of Relaxed Linear Adversarial Concept Erasure (RLACE). Given a dataset X of dense representation

Shauli Ravfogel 4 Apr 13, 2022
A Software Framework for Neuromorphic Computing

A Software Framework for Neuromorphic Computing

Lava 338 Dec 26, 2022
Required for a machine learning pipeline data preprocessing and variable engineering script needs to be prepared

Feature-Engineering Required for a machine learning pipeline data preprocessing and variable engineering script needs to be prepared. When the dataset

kemalgunay 5 Apr 21, 2022
This is my implementation on the K-nearest neighbors algorithm from scratch using Python

K Nearest Neighbors (KNN) algorithm In this Machine Learning world, there are various algorithms designed for classification problems such as Logistic

sonny1902 1 Jan 08, 2022
ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, MLOps and Data-Management

ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T

ClearML 4k Jan 09, 2023
PyHarmonize: Adding harmony lines to recorded melodies in Python

PyHarmonize: Adding harmony lines to recorded melodies in Python About To use this module, the user provides a wav file containing a melody, the key i

Julian Kappler 2 May 20, 2022
This is an auto-ML tool specialized in detecting of outliers

Auto-ML tool specialized in detecting of outliers Description This tool will allows you, with a Dash visualization, to compare 10 models of machine le

1 Nov 03, 2021
Titanic Traveller Survivability Prediction

The aim of the mini project is predict whether or not a passenger survived based on attributes such as their age, sex, passenger class, where they embarked and more.

John Phillip 0 Jan 20, 2022
InfiniteBoost: building infinite ensembles with gradient descent

InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De

Alex Rogozhnikov 183 Jan 03, 2023
Decision Weights in Prospect Theory

Decision Weights in Prospect Theory It's clear that humans are irrational, but how irrational are they? After some research into behavourial economics

Cameron Davidson-Pilon 32 Nov 08, 2021
Crypto-trading - ML techiques are used to forecast short term returns in 14 popular cryptocurrencies

Crypto-trading - ML techiques are used to forecast short term returns in 14 popular cryptocurrencies. We have amassed a dataset of millions of rows of high-frequency market data dating back to 2018 w

Panagiotis (Panos) Mavritsakis 4 Sep 22, 2022
This repository has datasets containing information of Uber pickups in NYC from April 2014 to September 2014 and January to June 2015. data Analysis , virtualization and some insights are gathered here

uber-pickups-analysis Data Source: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city Information about data set The dataset contain

B DEVA DEEKSHITH 1 Nov 03, 2021
Price forecasting of SGB and IRFC Bonds and comparing there returns

Project_Bonds Project Title : Price forecasting of SGB and IRFC Bonds and comparing there returns. Introduction of the Project The 2008-09 global fina

Tishya S 1 Oct 28, 2021
Simple data balancing baselines for worst-group-accuracy benchmarks.

BalancingGroups Code to replicate the experimental results from Simple data balancing baselines achieve competitive worst-group-accuracy. Replicating

Facebook Research 29 Dec 02, 2022
A benchmark of data-centric tasks from across the machine learning lifecycle.

A benchmark of data-centric tasks from across the machine learning lifecycle.

61 Dec 28, 2022
A Lucid Framework for Transparent and Interpretable Machine Learning Models.

Currently a Beta-Version lucidmode is an open-source, low-code and lightweight Python framework for transparent and interpretable machine learning mod

lucidmode 15 Aug 12, 2022
Interactive Parallel Computing in Python

Interactive Parallel Computing with IPython ipyparallel is the new home of IPython.parallel. ipyparallel is a Python package and collection of CLI scr

IPython 2.3k Dec 30, 2022
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort

Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort

2.3k Jan 04, 2023